Multi-modular Bayesian inference with misspecified models has some features which distinguish it from misspecification in single module settings. [1]} gave an early “modularization" analysis. Markov melding [2]} and Bayesian melding [3]} can be characterised as dealing with priors which conflict across modules. In our own work
we assume that modules have been identified as either misspecified or well-specified. This may be the conclusion of a first stage Bayesian analysis of the overall multi-modular model. A typical and well-founded objective is to estimate the parameters of a well-specified module making careful use of information from misspecified modules.
